CTNF 19/105,345 CTNF 96827 DETAILED ACTION This Office Action is in response to the communication filed on 02/21/2025. Claims 1-15 and 32-33 are pending. Claims 1-6 and 8-15 have been amended. Claims 16-32 have been cancelled. Claims 32-33 are new. Claims 1-15 and 32-33 are rejected. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Notes The dependent claim preambles are inconsistent. Claims 2, 7 and 10-12 read “the method of claim” Claims 3-6 and 13-14 read “the method as claimed in claim” It is not clear if claims 15 and 32-33 are intended to be dependent or independent claims. Claim Objections 07-29-01 AIA Claim s 1 and 9-11 are objected to because of the following informalities: Claim 1 and 9 reads “determining anomaly” which is grammatically incorrect. Claims 10 and 11 read “determining is anomaly” and “determining is not anomaly” which are grammatically incorrect. A claim which depends from a dependent claim should not be separated by any claim which does not also depend from said dependent claim. It should be kept in mind that a dependent claim may refer to any preceding independent claim. In general, applicant's sequence will not be changed. See MPEP § 608.01(n). Claim 12 depends form claim 10 and is separated by claim 11. Claim 14 depends form claim 12 and is separated by claim 13 . Appropriate correction is required. Claim Rejections - 35 USC § 112 07-30-02 AIA The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. 07-34-01 Claims 5 and 10-14 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. 07-34-05 Claim 5 recites the limitation "context data". There is insufficient antecedent basis for this limitation in the claim. Claims 10 and 11 recite “the action” it not clear which of the “two different actions” recited in claim 9 is being used as antecedent basis for “the action” in claims 10 and 11. There is insufficient antecedent basis for this limitation in the claim. Claim 12 recites “the actuator” and “the application”. There is insufficient antecedent basis for this limitation in the claim. 07-34-05 Claim 13 recites the limitation "the receiver person". There is insufficient antecedent basis for this limitation in the claim. Claim 14 recites the limitation "the logging" and “the updated policy configuration”. There is insufficient antecedent basis for this limitation in the claim. 07-34-07 AIA The claims are generally narrative and indefinite, failing to conform with current U.S. practice. They appear to be a literal translation into English from a foreign document and are replete with grammatical and idiomatic errors. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1 and 8-9 (and claims 2-7, 10-15 and 32-33) are rejected under 35 U.S.C. 101 because the claimed invention is directed to mental process – abstract idea without significantly more. The claims recite determining anomaly. This judicial exception is not integrated into a practical application because the steps recited in claim limitations, under the broadest reasonable interpretation, could be performed in the human mind or using paper and pencil therefore the claims fall within the “Mental Processes” grouping of abstract ideas. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements are obtaining data, applying analysis, and transmitting results. The additional element of obtaining sensory data and transmitting a result are considered to be data gathering and outputting which are insignificant extra solution activities and applying the payload-based analysis or packet-based analysis are M/L based models that are mere instructions to implement the abstract idea on a computer. The additional elements when reconsidered individually and as an ordered combination do not amount to significantly more than the abstract idea under because the sender note, receiver node and network node are considered to be generic components or generally linking the use of the abstract idea to the particular technological environment or field of use of computer networks as discussed above. The payload-based analysis or packet-based analysis are M/L based models that are mere instructions to implement the abstract idea on a computer. See the recitation of “apply it” in MPEP 2106.05(f). Additionally, the obtaining and transmitting steps are insignificant pre and post extra solution activities (i.e. data gathering and outputting) since receiving information and outputting information are well understood, routine and conventional (WURC). Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-15 AIA Claim s 1-2, 8-15 and 32-33 are rejected under 35 U.S.C. 102( a)(1 ) as being Anticipated by Jha (U.S. 20130247194 ) . Regarding claim 1, Jha discloses: A method for detecting security attacks in Internet of Senses (IoS) applications performed by a network node, the method comprising: (Jha [0005-0012, 0028, 0089-0109, 0163-0178] teaches a method including an anomaly detector which detects attacks) obtaining, from a sender node, sensory data and at least one of network data or context data; (Jha [0005-0012, 0028, 0089-0109, 0120-0146, 0163-0178] teaches detect an anomaly by analyzing the communications devices including sensors which obtain and communicate (sensory) data and obtaining data such as physical and behavioral data (sensory) that is used for payload (sensory/context) and packed (network) based analysis) determining anomaly by applying at least one of: (Jha [0005-0012, 0028, 0089-0109, 0120-0146, 0163-0178] teaches detect an anomaly by analyzing the communications devices including sensors which obtain and communicate (sensory) data and obtaining data such as physical and behavioral data (sensory) that is used for payload (sensory/context) and packed (network) based analysis) a payload-based analysis to at least one of the sensory data or the context data; or (Jha [0005-0012, 0104-0112, 0120-0121, 0150-0178] teaches determining anomalies includes analysis of the behavioral anomalies (payload-based)) a packet-based analysis to the network data, (Jha [0005-0012, 0104-0112, 0113-0121, 0150-0178] teaches determining anomalies includes analysis of the physical anomalies (packet-based)) wherein the payload-based analysis analyzes a payload of data packets, and wherein the packet-based analysis analyzes a pattern of data packet traffic; and (Jha [0005-0012, 0098-0103, 0113-0121, 0150-0178] teaches that behavioral anomalies (payload-based) analysis includes analyzing the payload of the packets behavior and physical anomalies (packet-based) includes analyzing the signal to determine abnormalities in the traffic by comparing against historical of normal traffic (pattern of traffic)) transmitting, to a receiver node, a result of the determining. (Jha [0005-0012, 0150-0178] teaches Attack Detection and Reaction including transmitting a signal to block the anomalous transmission to the PHS (receiver node) when an anomalous transmission is detected) Regarding claim 8, Jha discloses: A method for detecting security attacks in Internet of Senses (IoS) applications performed by a sender node, the method comprising: (Jha [0005-0012, 0028, 0089-0109, 0163-0178] teaches a method including an anomaly detector which detects attacks) obtaining sensory data and at least one of network data or context data; and (Jha [0005-0012, 0028, 0089-0109, 0120-0146, 0163-0178] teaches detect an anomaly by analyzing the communications devices including sensors which obtain and communicate (sensory) data and obtaining data such as physical and behavioral data (sensory) that is used for payload (sensory/context) and packed (network) based analysis) transmitting the sensory data and at least one of the network data or the context data to a network node which determines an anomaly by applying at least one of: (Jha [0005-0012, 0028, 0089-0109, 0120-0146, 0163-0178] teaches detect an anomaly by analyzing the communications devices including sensors which obtain and communicate (sensory) data and obtaining data such as physical and behavioral data (sensory) that is used for payload (sensory/context) and packed (network) based analysis) a payload-based analysis to at least one of the sensory data or the context data; or (Jha [0005-0012, 0104-0112, 0120-0121, 0150-0178] teaches determining anomalies includes analysis of the behavioral anomalies (payload-based)) a packet-based analysis to the network data. (Jha [0005-0012, 0104-0112, 0113-0121, 0150-0178] teaches determining anomalies includes analysis of the physical anomalies (packet-based)) Regarding claim 9, Jha discloses: A method for detecting security attacks in Internet of Senses (IoS) applications performed by a receiver node, the method comprising: (Jha [0005-0012, 0028, 0089-0109, 0163-0178] teaches a method including an anomaly detector which detects attacks) obtaining, from a network node, a result of determining anomaly determined by applying at least one of: (Jha [0005-0012, 0028, 0089-0109, 0120-0146, 0163-0178] teaches detect an anomaly by analyzing the communications devices including sensors which obtain and communicate (sensory) data and obtaining data such as physical and behavioral data (sensory) that is used for payload (sensory/context) and packed (network) based analysis and generating a corresponding result) a payload-based analysis to at least one of a sensory data or a context data obtained by a sender node; or (Jha [0005-0012, 0104-0112, 0120-0121, 0150-0178] teaches determining anomalies includes analysis of the behavioral anomalies (payload-based)) a packet-based analysis to a network data obtained by the sender node; and (Jha [0005-0012, 0104-0112, 0113-0121, 0150-0178] teaches determining anomalies includes analysis of the physical anomalies (packet-based)) initiating one of at least two different actions depending on the result of the determining anomaly. (Jha [0005-0012, 0150-0178] teaches Attack Detection and Reaction including transmitting a signal to block the anomalous transmission to the PHS (receiver node) when an anomalous transmission is detected and an action is taken including blocking or allowing the transmission, depending on the result of the determining) Claim 15 recites limitations substantially similar in scope as claim 1 above, therefore, is also rejected under the same rationale set forth above. Additionally claim 15 discloses: A non-transitory computer-readable medium storing thereon a computer program comprising code portions that, when executed on at least one processing circuitry, configure the processing circuitry to perform the method of claim 1. (Jha [0177] teaches the methods or flow charts provided herein may be implemented in a computer program, software, or firmware incorporated in a computer-readable (non-transitory) storage medium for execution by a general-purpose computer or a processor) Claim 32 recites limitations substantially similar in scope as claim 8 above, therefore, is also rejected under the same rationale set forth above. Additionally claim 32 discloses: A non-transitory computer-readable medium storing thereon a computer program comprising code portions that, when executed on at least one processing circuitry, configure the processing circuitry to perform the method of claim 8. (Jha [0177] teaches the methods or flow charts provided herein may be implemented in a computer program, software, or firmware incorporated in a computer-readable (non-transitory) storage medium for execution by a general-purpose computer or a processor) Claim 33 recites limitations substantially similar in scope as claim 9 above, therefore, is also rejected under the same rationale set forth above. Additionally claim 33 discloses: A non-transitory computer-readable medium storing thereon a computer program comprising code portions that, when executed on at least one processing circuitry, configure the processing circuitry to perform the method of claim 9. (Jha [0177] teaches the methods or flow charts provided herein may be implemented in a computer program, software, or firmware incorporated in a computer-readable (non-transitory) storage medium for execution by a general-purpose computer or a processor) Regarding claim 2, Jha discloses all the limitations of claim 1, Jha additionally discloses: The method of claim 1, further comprising: obtaining additional data from the receiver node to be used in the determining. (Jha [0005-0012, 0089-0090, 0098-0112, 0150-0178] teaches obtaining multiple (additional) pieces of data form the PHS’s including RSSI, TOA, DTOA, AOA and analyzes whether the PHS is in compliance with the security policies) Regarding claim 10, Jha discloses all the limitations of claim 9, Jha additionally discloses: The method of claim 9, wherein the action is notifying, if the result of the determining is anomaly, a receiver person. (Jha [0009-0011, 0090-0094, 0108] teaches warning the patient when an abnormality is detected) Regarding claim 11, Jha discloses all the limitations of claim 9, Jha additionally discloses: The method of claim 9, wherein the action is transmitting, if the result of the determining is not anomaly, the sensory data to an actuator or to an application. (Jha [0005-0011, 0028, 0108-0111, 0151-0171] teaches if no anomaly is found, the signal is deemed to be safe and granted access to the target PHS device (actuator for therapy deliver)) Regarding claim 12, Jha discloses all the limitations of claim 10, Jha additionally discloses: The method of claim 10, wherein the receiver person performs either: blocking the sensory data; or initiating a transmission of the sensory data to the actuator or to the application. (Jha [0094, 0107, 0144] teaches the suspicious transmission is blocked before it can complete and succeed in altering the state of the devices) Regarding claim 13, Jha discloses all the limitations of claim 9, Jha additionally discloses: The method as claimed in claim 9, wherein the receiver person performs at least one of: logging the sensory data; or updating a pre-determined policy configuration which defines measures to be taken in response to the result of the determining and parameters to be used in the determining by the network node. (Jha [0005-0011, 0083, 0106-0107, 0115, 0172] teaches logging data and patients approving/customizing parameters according to condition patient's condition and environment) Regarding claim 14, Jha discloses all the limitations of claim 12, Jha additionally discloses: The method as claimed in claim 12, further comprising transmitting at least one of: a result of the logging; or the updated policy configuration to the network node. (Jha [0005-0011, 0083, 0106-0107, 0115-0121, 0172] teaches logging data, resulting in logged data which is then transmitted for comparison purposes, and approving/customizing/updating parameters according to condition patient's condition and environment) Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim s 3-6 are rejected under 35 U.S.C. 103 as being unpatentable over Jha (U.S. 20130247194 ) in view of Furman (U.S. 20180012009) . Regarding claim 3, Jha discloses all the limitations of claim 1, Jha does not explicitly disclose: The method as claimed in claim 1, wherein the sensory data is based on at least one of touch, smell, taste or temperature. However, in the same field of endeavor Furman discloses: The method as claimed in claim 1, wherein the sensory data is based on at least one of touch, smell, taste or temperature. (Furman [0019-0025, 0041-0043] teaches sensor can be tactile, haptic, EEG, taste, smell and other olfactory sensors) Jha and Furman are analogous art because they are from the same field of endeavor cybersecurity associated with brain computer interface systems. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Jha and Furman before him or her, to modify the method of Jha to include the olfactory sensors of Furman because it will allow for olfactory inputs to be provided in the mental-physical data links. The motivation for doing so would be [“ enable metadata extraction from the real world via monitoring of neural signals, and executing actions based on the extracted metadata”; “enable iterative improvement of mental-physical data links”; “performance of brain computer interface devices can be improved by generating a user-specific calibration model”] (Paragraph 0027-0032 by Furman)]. Therefore, it would have been obvious to combine Jha and Furman to obtain the invention as specified in the instant claim. Regarding claim 4, Jha discloses all the limitations of claim 1, Jha does not explicitly disclose: The method as claimed in claim 1, wherein the context data is based on at least one of environment, temperature, time, location, energy consumption or aim of communication. However, in the same field of endeavor Furman discloses: The method as claimed in claim 1, wherein the context data is based on at least one of environment, temperature, time, location, energy consumption or aim of communication. (Furman [0038-0042, 0041-0043] teaches additional sensor data including environmental, temperature, humidity, non-brain activity-derived, GPS, reaction time) It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify with Furman for similar reasons as cited in claim 3. Regarding claim 5, Jha discloses all the limitations of claim 1, Jha additionally discloses: The method as claimed in claim 1, wherein the payload-based analysis uses a machine learning, ML, model trained with sensory data or context data or both. (Jha [0005-0012, 0104-0112, 0120-0121, 0150-0178, 0192] analysis of the behavioral anomalies (payload-based) and learning the characteristics of normal behavior and physical characteristics of the communications between the medical devices) Jha does not explicitly disclose: uses a machine learning, ML, model However, in the same field of endeavor Furman discloses: uses a machine learning, ML, model (Furman [0049-0054] using a machine learning model) It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify with Furman for similar reasons as cited in claim 3. Regarding claim 6, Jha discloses all the limitations of claim 1, Jha additionally discloses: The method as claimed in claim 1, wherein the packet-based analysis uses a machine learning, ML, model trained with network data. (Jha [0005-0012, 0104-0112, 0113-0121, 0150-0178, 0192] teaches analysis of the physical anomalies (packet-based) and learning the characteristics of normal behavior and physical characteristics of the communications between the medical devices) Jha does not explicitly disclose: uses a machine learning, ML, model However, in the same field of endeavor Furman discloses: uses a machine learning, ML, model (Furman [0049-0054] using a machine learning model) It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify with Furman for similar reasons as cited in claim 3 . 07-21-aia AIA Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Jha (U.S. 20130247194 ) in view of Furman (U.S. 20180234302) and in further view of James (U.S. 20180234302) . Regarding claim 7, Jha in view of Furman discloses all the limitations of claim 6, While Furman teaches a time window and machine learning model, Jha in view of Furman does not explicitly disclose: The method of claim 6, wherein a feature set extracted from a selected sample, w, of network traffic features within a pre-determined time interval, t, is fed into the ML model. However, in the same field of endeavor James discloses: The method of claim 6, wherein a feature set extracted from a selected sample, w, of network traffic features within a pre-determined time interval, t, is fed into the ML model. (James [0054-0060, 0071-0074, 0138-0154] teaches obtaining data from a source by traffic/event monitoring then feeding the data into a ML model. The data is provided to modules which create a dataset/frame (w) corresponding to a specific window (t)) Jha in view of Furman and James are analogous art because they are from the same field of endeavor of information security. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of Jha in view of Furman and James before him or her, to modify the method of Jha in view of Furman to include the training dataset of James an important consideration for network monitoring is speed and performance. The motivation for doing so would be [“provide monitoring and security against rogue devices by observing their behavior in the network and using machine learning to classify behavior as normal, rogue or suspicious” and “ensures that the performance is not compromised”] (Paragraph 0031, 0065, 0073 by James)]. Therefore, it would have been obvious to combine Jha in view of Furman and James to obtain the invention as specified in the instant claim. Conclusion 07-96 The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Wu 2005-12-08 (U.S. 20060129277) teaches an embedded internet robot system controlled by brain waves, wherein the brain-computer interface and the internet robot system cooperate with the alertness level detection technology and the instruction translation technology, and thereby, the user can control a distal-end robot purely via consciousness activities and can interact with the environment as if there were an entity representing the user's consciousness appearing in the distal end. The seriously disabled person can regain his expressive ability via the present invention. Further, the present invention can also be applied to a multi-player interactive game system. Alkurd 2021-08-26 (U.S. 20210266781) teaches a method and system for managing and allocating wireless network resources to optimize User satisfaction. One aspect of the invention is directed to a system comprising a wireless base station; a user device; and a wireless network connecting said wireless base-station to said user device; said wireless base station being operable: to employ a ‘zone of tolerance’ to model user satisfaction; and to respond to a request from said user device to access network resources, by allocating network resources based on said ‘zone of tolerance’ model. Other aspects of the invention are also shown and described including a system and method of allocating network resources based on an AI-Enabled and Big Data-Driven Multi-Objective Optimization Process. Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS A CARNES whose telephone number is (571)272-4378. The examiner can normally be reached Monday-Friday. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shewaye Gelagay can be reached at (571) 272-4219. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. THOMAS A. CARNES Examiner Art Unit 2436 /THOMAS A CARNES/Examiner, Art Unit 2436 Application/Control Number: 19/105,345 Page 2 Art Unit: 2436 Application/Control Number: 19/105,345 Page 3 Art Unit: 2436 Application/Control Number: 19/105,345 Page 4 Art Unit: 2436 Application/Control Number: 19/105,345 Page 5 Art Unit: 2436 Application/Control Number: 19/105,345 Page 6 Art Unit: 2436 Application/Control Number: 19/105,345 Page 7 Art Unit: 2436 Application/Control Number: 19/105,345 Page 8 Art Unit: 2436 Application/Control Number: 19/105,345 Page 9 Art Unit: 2436 Application/Control Number: 19/105,345 Page 10 Art Unit: 2436 Application/Control Number: 19/105,345 Page 11 Art Unit: 2436 Application/Control Number: 19/105,345 Page 12 Art Unit: 2436 Application/Control Number: 19/105,345 Page 13 Art Unit: 2436 Application/Control Number: 19/105,345 Page 14 Art Unit: 2436 Application/Control Number: 19/105,345 Page 15 Art Unit: 2436 Application/Control Number: 19/105,345 Page 16 Art Unit: 2436 Application/Control Number: 19/105,345 Page 17 Art Unit: 2436 Application/Control Number: 19/105,345 Page 18 Art Unit: 2436
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